Presentation: Tweet"Making Big Data Useful Data"
With Big Data becoming more and more the norm in many companies, there is added complexity not only to the systems logging and storing the data, but also to the logic of and reasoning of the end user. The business user would often like to dig deeper into the data, whereas the developer wants to make sure that the data is optimized for easy management. What and who should determine the trade-off? Our goal has been to try to create a development environment that allows for making that distinction on a case by case basis. However with rapid growth and continued increased popularity this remains to be a challenge and prioritization is a constant obstacle. Front-end and reporting is the last step facing the end-user, and many times the decisions affecting the interface were made several steps upstream. Today we have aggregation in the data warehouse, intermediate cubes as well as aggregation in the reporting tools. In order to manage the many variations of business needs, as well as levels of aggregations layer that our different requests contain, we have strived to make our development environment the constant. It is standardized enough to create stability, yet flexible enough to allow for creativity. I would like to speak a little about how we view the challenges of our Big Data and how we systematically address them in order to provide our end-users with the right information at the right time.
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